Notes

  • ‘Support’ indicates agreement with question phrasing stated in plot title: combining all relevant agreement levels from the question.

Setup

knitr::opts_chunk$set(echo = TRUE) # Set this to TRUE to show code.
knitr::opts_chunk$set(warning = FALSE, message = FALSE) # This hides some printed outputs
# Packages
library(tidyverse)
library(ggplot2)
library(rmarkdown)
library(scales)
library(ggrepel)
# Reading and merging

# Question files
for (i in 1:15) {
  file_name <- paste0("question_", i, ".csv")

  var_name <- paste0("question_", i)

  assign(var_name, read.csv(file_name))
}

national_data <- read.csv("national_data_v1.csv")
national_data <- rename(national_data, ISO = iso2_code)

# Matching to national data
for (i in 1:15) {
  question_var_name <- paste("question", i, sep = "_")

  assign(question_var_name, head(left_join(get(question_var_name), national_data, by = "ISO"), -1))
}

# Creating gender gap variable
for (i in 1:15) {
  question_var_name <- paste("question", i, sep = "_")

  assign(question_var_name, mutate(get(question_var_name),
    gender_gap = Female - Male
  ))
}
# Filter main
for (i in 1:15) {
  question_var_name <- paste("question", i, sep = "_")
  filtered_question_var_name <- paste("filtered_question", i, sep = "_")

  temp_data <- get(question_var_name)
  filtered_data <- temp_data[!is.na(temp_data$Overall), ]

  assign(filtered_question_var_name, filtered_data)
}

Headline stats distribution

# Assuming 'filtered_questions' is a list of data frames where each data frame corresponds to a question's data
filtered_questions <- list(filtered_question_1, filtered_question_2, filtered_question_3, filtered_question_4, filtered_question_5, filtered_question_6, filtered_question_7, filtered_question_8, filtered_question_9, filtered_question_10, filtered_question_11, filtered_question_12, filtered_question_13, filtered_question_14, filtered_question_15)

# Titles for each plot
plot_titles <- c(
  "Question 1 (think often about climate change): Distribution of support across countries",
  "Question 2 (more worried c/w last year) : Distribution of support across countries",
  "Question 3 (worried about next gen)  : Distribution of support across countries",
  "Question 4 (extreme weather - worse) : Distribution of support across countries",
  "Question 5 (affected big decisions) : Distribution of support across countries",
  "Question 6 (how well country addressing) : Distribution of support across countries",
  "Question 7 (how well are big businesses addressing) : Distribution of support across countries",
  "Question 8 (gov't has most impact addressing) : Distribution of support across countries",
  "Question 9 (country should strengthen commitments) : Distribution of support across countries",
  "Question 10 (country should replace fossil fuels more quickly) : Distribution of support across countries",
  "Question 11 (country should protect and restore nature) : Distribution of support across countries",
  "Question 12 (country should provide support to protect people at risk) : Distribution of support across countries",
  "Question 13 (countries should work together) : Distribution of support across countries",
  "Question 14 (rich countries should give more) : Distribution of support across countries",
  "Question 15 (schools should teach more) : Distribution of support across countries"
)

# Function to create plot
create_plot <- function(data, title) {
  ggplot(data, aes(x = Overall)) +
    geom_histogram(binwidth = 0.5, fill = "#add8e6") +
    scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
    theme_minimal() +
    theme(
      plot.title = element_text(margin = margin(b = 20)),
      legend.position = "bottom",
      axis.title.x = element_text(margin = margin(t = 10)),
      axis.title.y = element_text(margin = margin(r = 10)),
      axis.line.x = element_blank(),
      axis.ticks.x = element_blank()
    ) +
    labs(
      title = title,
      x = "Support",
      y = "Frequency"
    )
}

# Loop to create each plot
for (i in 1:length(filtered_questions)) {
  print(create_plot(filtered_questions[[i]], plot_titles[i]))
}

Policy support vs CO2

# Question 9
ggplot(filtered_question_9, aes(x = co2_per_capita_owid, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst CO2 per capita",
    x = "Annual CO2 per capita (tonnes per person)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = co2_per_capita_owid, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst CO2 per capita",
    x = "Annual CO2 per capita (tonnes per person)",
    y = "Question 10 support"
  )

Policy support vs GDP pc

# Question 9
ggplot(filtered_question_9, aes(x = real_gdp_ppp_pc_cia, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst GDP per capita",
    x = "GDP PPP per capita",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = real_gdp_ppp_pc_cia, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst GDP per capita",
    x = "GDP PPP per capita",
    y = "Question 10 support"
  )

Policy support vs GDP PPP

# Question 9
ggplot(filtered_question_9, aes(x = real_gdp_ppp_cia, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst GDP",
    x = "GDP PPP",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = real_gdp_ppp_cia, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst GDP",
    x = "GDP PPP",
    y = "Question 10 support"
  )

Policy support vs oil production

# Question 9
ggplot(filtered_question_9, aes(x = oil_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst oil production",
    x = "Oil production (terawatt-hours)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = oil_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst oil production",
    x = "Oil production (terawatt-hours)",
    y = "Question 10 support"
  )

Policy support vs coal production

# Question 9
ggplot(filtered_question_9, aes(x = coal_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst coal production",
    x = "Coal production (terawatt-hours)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = coal_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst coal production",
    x = "Coal production (terawatt-hours)",
    y = "Question 10 support"
  )

Policy support vs subset of coal producers

# Top 10%
top_coal <- quantile(filtered_question_9$coal_production_ei, 0.80, na.rm = T)
filtered_question_9_coal <- subset(filtered_question_9, coal_production_ei >= top_coal)
filtered_question_10_coal <- subset(filtered_question_10, coal_production_ei >= top_coal)
filtered_question_9_coal_nochina <- subset(filtered_question_9_coal, Country != "China")
filtered_question_10_coal_nochina <- subset(filtered_question_10_coal, Country != "China")

# Question 9
ggplot(filtered_question_9_coal, aes(x = coal_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text_repel(aes(label = Country), nudge_y = 6, size = 3, 
                  segment.color = 'grey50') +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst coal production: top 20% producers",
    x = "Coal production (terawatt-hours)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10_coal, aes(x = coal_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text_repel(aes(label = Country), nudge_y = 6, size = 3, 
                  segment.color = 'grey50') +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst coal production: top 20% producers",
    x = "Coal production (terawatt-hours)",
    y = "Question 10 support"
  )

# Without China
# Question 9
ggplot(filtered_question_9_coal_nochina, aes(x = coal_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text_repel(aes(label = Country), nudge_y = 6, size = 3, 
                  segment.color = 'grey50') +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst coal production: top 20% producers w/o China",
    x = "Coal production (terawatt-hours)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10_coal_nochina, aes(x = coal_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text_repel(aes(label = Country), nudge_y = 6, size = 3, 
                  segment.color = 'grey50') +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst coal production: top 20% producers w/o China",
    x = "Coal production (terawatt-hours)",
    y = "Question 10 support"
  )

# Check significance
topcoal9_nochina <- lm(Overall ~ coal_production_ei, data = filtered_question_9_coal_nochina)
topcoal10_nochina <- lm(Overall ~ coal_production_ei, data = filtered_question_10_coal_nochina)

summary(topcoal9_nochina)
## 
## Call:
## lm(formula = Overall ~ coal_production_ei, data = filtered_question_9_coal_nochina)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -15.391  -9.483   2.914   6.126  13.907 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        83.221056   4.484149  18.559 1.75e-08 ***
## coal_production_ei -0.002471   0.001905  -1.297    0.227    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.47 on 9 degrees of freedom
## Multiple R-squared:  0.1574, Adjusted R-squared:  0.06383 
## F-statistic: 1.682 on 1 and 9 DF,  p-value: 0.2269
summary(topcoal10_nochina)
## 
## Call:
## lm(formula = Overall ~ coal_production_ei, data = filtered_question_10_coal_nochina)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -43.841  -3.836  -0.230  13.123  21.839 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        69.212859   8.810464   7.856 2.56e-05 ***
## coal_production_ei -0.003608   0.003743  -0.964     0.36    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 20.57 on 9 degrees of freedom
## Multiple R-squared:  0.09356,    Adjusted R-squared:  -0.007153 
## F-statistic: 0.929 on 1 and 9 DF,  p-value: 0.3603

Policy support vs gas production

# Question 9
ggplot(filtered_question_9, aes(x = gas_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst gas production",
    x = "Gas production (terawatt-hours)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = gas_production_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = comma_format()) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst gas production",
    x = "Gas production (terawatt-hours)",
    y = "Question 10 support"
  )

Policy support vs renewables

# Question 9
ggplot(filtered_question_9, aes(x = renewable_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_9$renewable_ei, na.rm = TRUE), max(filtered_question_9$renewable_ei, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst renewables",
    x = "Renewables (share of energy consumption)",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = renewable_ei, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_10$renewable_ei, na.rm = TRUE), max(filtered_question_10$renewable_ei, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst renewables",
    x = "Renewables (share of energy consumption)",
    y = "Question 10 support"
  )

HDI overall

filtered_question_1$hdi_undp <- as.numeric(filtered_question_1$hdi_undp)
filtered_question_2$hdi_undp <- as.numeric(filtered_question_2$hdi_undp)
filtered_question_3$hdi_undp <- as.numeric(filtered_question_3$hdi_undp)
filtered_question_4$hdi_undp <- as.numeric(filtered_question_4$hdi_undp)
filtered_question_5$hdi_undp <- as.numeric(filtered_question_5$hdi_undp)
filtered_question_6$hdi_undp <- as.numeric(filtered_question_6$hdi_undp)
filtered_question_7$hdi_undp <- as.numeric(filtered_question_7$hdi_undp)
filtered_question_8$hdi_undp <- as.numeric(filtered_question_8$hdi_undp)
filtered_question_9$hdi_undp <- as.numeric(filtered_question_9$hdi_undp)
filtered_question_10$hdi_undp <- as.numeric(filtered_question_10$hdi_undp)
filtered_question_11$hdi_undp <- as.numeric(filtered_question_11$hdi_undp)
filtered_question_12$hdi_undp <- as.numeric(filtered_question_12$hdi_undp)
filtered_question_13$hdi_undp <- as.numeric(filtered_question_13$hdi_undp)
filtered_question_14$hdi_undp <- as.numeric(filtered_question_14$hdi_undp)
filtered_question_15$hdi_undp <- as.numeric(filtered_question_15$hdi_undp)

filtered_questions <- list(
  filtered_question_1, filtered_question_2, filtered_question_3,
  filtered_question_4, filtered_question_5, filtered_question_6,
  filtered_question_7, filtered_question_8, filtered_question_9,
  filtered_question_10, filtered_question_11, filtered_question_12,
  filtered_question_13, filtered_question_14, filtered_question_15
)

create_plot <- function(data, title) {
  ggplot(data, aes(x = hdi_undp, y = Overall, colour = Region)) +
    geom_point() +
    geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
    geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
    scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
    scale_x_continuous(limits = c(min(data$hdi_undp, na.rm = TRUE), max(data$hdi_undp, na.rm = TRUE))) +
    theme_minimal() +
    theme(
      plot.title = element_text(margin = margin(b = 20)),
      legend.position = "bottom",
      axis.title.x = element_text(margin = margin(t = 10)),
      axis.title.y = element_text(margin = margin(r = 10))
    ) +
    labs(
      title = title,
      x = "HDI",
      y = paste("Support")
    )
}

for (i in seq_along(filtered_questions)) {
  print(create_plot(filtered_questions[[i]], plot_titles[i]))
}

HDI gender gap

# Question 3
ggplot(filtered_question_3, aes(x = hdi_undp, y = gender_gap, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(-25, 25)) +
  scale_x_continuous(limits = c(min(filtered_question_3$hdi_undp, na.rm = TRUE), max(filtered_question_3$hdi_undp, na.rm = TRUE))) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 3 (worried about next gen)  against HDI gender gap",
    x = "HDI",
    y = "Question 3 gender gap (women over men)"
  )

# Question 9
ggplot(filtered_question_9, aes(x = hdi_undp, y = gender_gap, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(-25, 25)) +
  scale_x_continuous(limits = c(min(filtered_question_9$hdi_undp, na.rm = TRUE), max(filtered_question_9$hdi_undp, na.rm = TRUE))) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst HDI gender gap",
    x = "HDI",
    y = "Question 9 gender gap (women over men)"
  )

# Question 10
ggplot(filtered_question_10, aes(x = hdi_undp, y = gender_gap, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(-25, 25)) +
  scale_x_continuous(limits = c(min(filtered_question_10$hdi_undp, na.rm = TRUE), max(filtered_question_10$hdi_undp, na.rm = TRUE))) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst HDI gender gap",
    x = "HDI",
    y = "Question 10 gender gap (women over men)"
  )

Policy support vs Islam

# Question 9
ggplot(filtered_question_9, aes(x = islam_pew, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_9$islam_pew, na.rm = TRUE), max(filtered_question_9$islam_pew, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst Islam",
    x = "Muslim pc of population",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = islam_pew, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_10$islam_pew, na.rm = TRUE), max(filtered_question_10$islam_pew, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst Islam",
    x = "Muslim pc of population",
    y = "Question 10 support"
  )

Experiences of climate change vs expression of experience

# Natural disasters
# Question 1
ggplot(filtered_question_1, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_1$natural_disasters_imf, na.rm = TRUE), max(filtered_question_1$natural_disasters_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 1 (think often about climate change)\nagainst natural disasters",
    x = "Natural disasters yearly average 2017-2022",
    y = "Question 1 support"
  )

# Question 2
ggplot(filtered_question_2, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_2$natural_disasters_imf, na.rm = TRUE), max(filtered_question_2$natural_disasters_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 2 (more worried c/w last year)\nagainst natural disasters",
    x = "Natural disasters yearly average 2017-2022",
    y = "Question 2 support"
  )

# Surface temp
# Question 1
ggplot(filtered_question_1, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_1$surface_temp_imf, na.rm = TRUE), max(filtered_question_1$surface_temp_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 1 (think often about climate change)\nagainst surface temp",
    x = "Mean surface temp change 1961-2021",
    y = "Question 1 support"
  )

# Question 2
ggplot(filtered_question_2, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_2$surface_temp_imf, na.rm = TRUE), max(filtered_question_2$surface_temp_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 2 (more worried c/w last year)\nagainst surface temp",
    x = "Mean surface temp change 1961-2021",
    y = "Question 2 support"
  )

Experiences of climate change vs policy support

# Natural disasters

# Question 9
ggplot(filtered_question_9, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$natural_disasters_imf, na.rm = TRUE), max(filtered_question_9$natural_disasters_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst natural disasters",
    x = "Natural disasters yearly average 2017-2022",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$natural_disasters_imf, na.rm = TRUE), max(filtered_question_10$natural_disasters_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst natural disasters",
    x = "Natural disasters yearly average 2017-2022",
    y = "Question 10 support"
  )

# Question 12
ggplot(filtered_question_12, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_12$natural_disasters_imf, na.rm = TRUE), max(filtered_question_12$natural_disasters_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 12 (country should provide support to protect people at risk)\nagainst natural disasters",
    x = "Natural disasters yearly average 2017-2022",
    y = "Question 12 support"
  )

# Surface temp
# Question 9
ggplot(filtered_question_9, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$surface_temp_imf, na.rm = TRUE), max(filtered_question_9$surface_temp_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst surface temp",
    x = "Mean surface temp change 1961-2021",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$surface_temp_imf, na.rm = TRUE), max(filtered_question_10$surface_temp_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst surface temp",
    x = "Mean surface temp change 1961-2021",
    y = "Question 10 support"
  )

# Question 12
ggplot(filtered_question_12, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_12$surface_temp_imf, na.rm = TRUE), max(filtered_question_12$surface_temp_imf, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 12 (country should provide support to protect people at risk)\nagainst surface temp",
    x = "Mean surface temp change 1961-2021",
    y = "Question 12 support"
  )

Regime type

# Question 6
ggplot(filtered_question_6, aes(x = electdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_6$electdem_vdem, na.rm = TRUE), max(filtered_question_6$electdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 6 (how well country addressing)\nagainst Electoral democracy",
    x = "Electoral democracy score",
    y = "Question 6 support"
  )

ggplot(filtered_question_6, aes(x = libdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_6$libdem_vdem, na.rm = TRUE), max(filtered_question_6$libdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 6 (how well country addressing)\nagainst Liberal democracy",
    x = "Liberal democracy score",
    y = "Question 6 support"
  )

ggplot(filtered_question_6, aes(x = participdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_6$participdem_vdem, na.rm = TRUE), max(filtered_question_6$participdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 6 (how well country addressing)\nagainst participatory democracy",
    x = "Participatory democracy score",
    y = "Question 6 support"
  )

ggplot(filtered_question_6, aes(x = delibdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_6$delibdem_vdem, na.rm = TRUE), max(filtered_question_6$delibdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 6 (how well country addressing)\nagainst deliberative democracy",
    x = "Deliberative democracy score",
    y = "Question 6 support"
  )

ggplot(filtered_question_6, aes(x = egaldem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_6$egaldem_vdem, na.rm = TRUE), max(filtered_question_6$egaldem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 6 (how well country addressing)\nagainst egalitarian democracy",
    x = "Egalitarian democracy score",
    y = "Question 6 support"
  )

# Question 9
ggplot(filtered_question_9, aes(x = electdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$electdem_vdem, na.rm = TRUE), max(filtered_question_9$electdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst Electoral democracy",
    x = "Electoral democracy score",
    y = "Question 9 support"
  )

ggplot(filtered_question_9, aes(x = libdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$libdem_vdem, na.rm = TRUE), max(filtered_question_9$libdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst Liberal democracy",
    x = "Liberal democracy score",
    y = "Question 9 support"
  )

ggplot(filtered_question_9, aes(x = participdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$participdem_vdem, na.rm = TRUE), max(filtered_question_9$participdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst participatory democracy",
    x = "Participatory democracy score",
    y = "Question 9 support"
  )

ggplot(filtered_question_9, aes(x = delibdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$delibdem_vdem, na.rm = TRUE), max(filtered_question_9$delibdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst deliberative democracy",
    x = "Deliberative democracy score",
    y = "Question 9 support"
  )

ggplot(filtered_question_9, aes(x = egaldem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_9$egaldem_vdem, na.rm = TRUE), max(filtered_question_9$egaldem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 9 (country should strengthen commitments)\nagainst egalitarian democracy",
    x = "Egalitarian democracy score",
    y = "Question 9 support"
  )

# Question 10
ggplot(filtered_question_10, aes(x = electdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$electdem_vdem, na.rm = TRUE), max(filtered_question_10$electdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst Electoral democracy",
    x = "Electoral democracy score",
    y = "Question 10 support"
  )

ggplot(filtered_question_10, aes(x = libdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$libdem_vdem, na.rm = TRUE), max(filtered_question_10$libdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst Liberal democracy",
    x = "Liberal democracy score",
    y = "Question 10 support"
  )

ggplot(filtered_question_10, aes(x = participdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$participdem_vdem, na.rm = TRUE), max(filtered_question_10$participdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst participatory democracy",
    x = "Participatory democracy score",
    y = "Question 10 support"
  )

ggplot(filtered_question_10, aes(x = delibdem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$delibdem_vdem, na.rm = TRUE), max(filtered_question_10$delibdem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst deliberative democracy",
    x = "Deliberative democracy score",
    y = "Question 10 support"
  )

ggplot(filtered_question_10, aes(x = egaldem_vdem, y = Overall, colour = Region)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
  geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
  scale_x_continuous(limits = c(min(filtered_question_10$egaldem_vdem, na.rm = TRUE), max(filtered_question_10$egaldem_vdem, na.rm = TRUE))) +
  scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
  theme_minimal() +
  theme(
    plot.title = element_text(margin = margin(b = 20)),
    legend.position = "bottom",
    axis.title.x = element_text(margin = margin(t = 10)),
    axis.title.y = element_text(margin = margin(r = 10))
  ) +
  labs(
    title = "Question 10 (country should replace fossil fuels more quickly)\nagainst egalitarian democracy",
    x = "Egalitarian democracy score",
    y = "Question 10 support"
  )